Evidence map›Paper›PMID 33275675›Full record

ReviewHematology. American Society of Hematology. Education Program2020

Can pregnancy-adapted algorithms avoid diagnostic imaging for pulmonary embolism?

Wee-Shian Chan

Abstract readCase ReportsReview
In one paragraph

Review in Hematology. American Society of Hematology. Education Program, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Diagnosis of Pulmonary Embolism during Pregnancy.Diagnostics (Basel, Switzerland) · 2022
    Review
  4. Review
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Wee-Shian ChanBC Women's Hospital, University of British Columbia, Vancouver, BC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The low prevalence of pulmonary embolism (PE) among pregnant patients presenting with suspected PE implies that most of these patients will be found not have the disease. Given this low prevalence, excluding PE in this population has necessitated the use of sensitive and specific diagnostic imaging, such as computed tomography pulmonary angiography or ventilation-perfusion scanning. Recent studies suggest that a clinical prediction rule with D-dimer testing can also be used to exclude a subset of pregnant patients with suspected PE without the need for diagnostic imaging. The YEARS criteria, which consist of clinical signs and symptoms of deep venous thrombosis, hemoptysis, and PE as the most likely diagnosis (a subjective variable), combined with selective D-dimer levels, seem to safely exclude up to one-third of these patients without imaging. The revised Geneva rule using objective variables, combined with nonpregnancy cutoffs for D-dimer levels, offers some promise, although fewer patients avoided imaging (14%). These recent studies provide evidence in support of radiation avoidance for some patients; however, for most, imaging remains the only option. Future studies should focus on improving the safety and techniques of imaging modalities, in addition to improving the specificity of D-dimer testing and objective prediction rules. Studies assessing patients' and physicians' values, preferences, and risk perceptions are also required to assist clinicians in shared decision making when counseling pregnant patients with suspected PE.

Indexed as

AlgorithmsPregnancy Complications, CardiovascularPulmonary EmbolismAdultComputed Tomography AngiographyFemaleFibrin Fibrinogen Degradation ProductsHumansPregnancyFibrin Fibrinogen Degradation Productsfibrin fragment D

Identifiers

PMID33275675
PMCPMC7727560

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.